Create an object containing information about inverse chi-squared priors with possibly modeled degrees of freedom and scale parameters
pr_invchisq(df = 1, scale = 1, n = NULL, post = FALSE)An environment with information about the prior and possibly conditional posterior distribution(s), to be used by other package functions.
degrees of freedom parameter. This can be a numeric scalar or
vector of length n, the dimension of the parameter vector.
Alternatively, for a scalar degrees of freedom parameter,
df="modeled" or df="modelled" assign a default (gamma) prior
to the degrees of freedom parameter. For more control of this gamma prior a
list can be passed with some of the following components:
shape parameter of the gamma distribution
rate parameter of the gamma distribution
"RW" for random walk Metropolis-Hastings or "mala" for Metropolis-adjusted Langevin
(starting) scale of Metropolis-Hastings update
whether to adapt the scale of the proposal distribution during burnin to achieve better acceptance rates.
scalar or vector scale parameter. Alternatively,
scale="modeled" or scale="modelled" puts a default
chi-squared prior on the scale parameter. For more control on this
chi-squared prior a list can be passed with some of the following components:
degrees of freedom (scalar or vector)
scale (scalar or vector)
whether the modeled scale parameter of the inverse chi-squared
distribution is (a scalar parameter) common to all n parameters.
dimension, if known. For internal use only.
whether conditional posterior sampling function should be created. For internal use only.